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Reinforcement Learning for Sequential Decision and Optimal Control

Reinforcement Learning for Sequential Decision and Optimal Control
Free Download Reinforcement Learning for Sequential Decision and Optimal Control
English | 2023 | ISBN: 9811977836 | 484 Pages | PDF (True) | 23 MB
Have you ever wondered how AlphaZero learns to defeat the top human Go players? Do you have any clues about how an autonomous driving system can gradually develop self-driving skills beyond normal drivers? What is the key that enables AlphaStar to make decisions in Starcraft, a notoriously difficult strategy game that has partial information and complex rules? The core mechanism underlying those recent technical breakthroughs is reinforcement learning (RL), a theory that can help an agent to develop the self-evolution ability through continuing environment interactions. In the past few years, the AI community has witnessed phenomenal success of reinforcement learning in various fields, including chess games, computer games and robotic control. RL is also considered to be a promising and powerful tool to create general artificial intelligence in the future.






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